Lead Affordability Data Analytics Engineer

Raytheon; McKinney (TX); On-site; USD 108,000 - 205,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Life Insurance

Short-term Disability

Long-term Disability

401(k) match

Flexible Spending Accounts

Flexible work schedules

Employee Assistance Program

Employee Scholar Program

Parental Leave

Paid Time Off

Holidays

Job summary

Raytheon is seeking a Principal Affordability Data Analytics Engineer to lead advanced statistical and lifecycle cost analyses for affordability modeling. You will develop analytic frameworks, identify key cost drivers, and support Modelers and Leads with high-confidence datasets in an onsite McKinney, TX setting.

Responsibilities include integrating engineering, operations, and sustainment data, performing cost-behavior analyses, and providing outputs for CRIs and trade studies.

Qualifications

• Degree in Science, Technology, Engineering or Mathematics (STEM) is typically required.
• Experience with statistical analysis, including multivariate regression, forecasting, and/or distribution modeling.
• Experience analyzing cost structures across design, production, and sustainment phases.

Responsibilities

• Lead advanced analytics including multivariate regression, predictive modeling, and cost-driver decomposition.
• Develop analytical frameworks supporting RLPM phase reviews and affordability processes.
• Integrate multi-disciplinary data sources (engineering, operations, SCM, sustainment) for lifecycle insight.
• Identify fixed, variable, step, and learning-curve cost behaviors and their lifecycle implications.
• Produce analytical outputs supporting CRIs, trade studies, AoAs, and cost maturity assessments.
• Mentor earlier in career analysts in statistical techniques and affordability methods.

Skills

Multivariate regression

Forecasting

Cost-driver decomposition

Data integration

Statistical analysis

Mentoring analysts

Education

STEM degree

Job description

Raytheon is seeking a Principal Affordability Data Analytics Engineer to lead advanced statistical and lifecycle cost analyses for affordability modeling. You will develop analytic frameworks, identify key cost drivers, and support Modelers and Leads with high-confidence datasets in an onsite McKinney, TX setting.

Responsibilities include integrating engineering, operations, and sustainment data, performing cost-behavior analyses, and providing outputs for CRIs and trade studies.